Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this “breast-to-breast” metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.


Introduction
Development of metastatic disease is the most dreaded outcome for breast cancer.When breast cancer becomes metastatic, it is virtually incurable, and treatment is primarily palliative.Despite advances in early detection and treatment in the adjuvant settings, breast cancer patients sometimes develop metastatic disease.This is an important area with unmet need.Metastasis is a multi-step process encompassing the (1) local infiltration of tumor cells into the adjacent tissue, (2) trans-endothelial migration of cancer cells into vessels known as intravasation, (3) survival in the circulatory system, and (4) subsequent extravasation and proliferation in distant organs leading to colonization [1,2].Thorough understanding of the molecular underpinnings of breast cancer metastasis is essential for risk stratification and development of therapy.
Bilateral breast cancers, an uncommon form and accounting for 3-5% of all breast cancers cases, happens when women develop breast cancers in both breasts, with the second primary cancer in the contralateral breast being either synchronous or metachronous [3][4][5][6][7].Synchronous bilateral breast cancers are diagnosed 6-12 months apart and represent about 1% of breast cancers [8][9][10].Clinically, patients with synchronous bilateral breast cancers behaved similarly to those with unilateral breast cancers [11,12].However, in metachronous bilateral breast cancers, accounting for 2-3% of breast cancers [7,13], an adjuvant chemotherapy study reported a dual effect on reducing the risk of developing while worsening the prognosis of a second cancer that developed more than one year later [14].
Whole exome sequencing (WES) of primary and contralateral breast cancers showed a high mutational diversity between cancers [15].The current WES study of 16 sets of bilateral breast cancers revealed that some of them were clonally related, i.e., "breast-to-breast metastasis events", suggesting that these metastasis events represent initial efforts of primary breast tumors to acquire metastatic/spreading potentials.Since spreading breast cancer cells are returning to the same breast environment these cells have originated from, we speculate that this represents a circumscribed spectrum of cancer metastasis without having to incur extensive genomic changes required for full-blown metastasis.In these "mother to daughter" primary breast tumor pairs, only a limited number of somatic mutations were acquired in the daughter tumors which in essence were metastatic deposits but not primary breast cancers (0-8), suggesting a finite number of mutations were sufficient to orchestrate/initiate metastasis.One such mutation was SIVA-D160N.
SIVA apoptosis inducing factor (SIVA) was first identified via a yeast two-hybrid screening with CD27, a member of the tumor necrosis factor receptor family, when it was used as the bait [16].In previous studies, SIVA, also known as CD27-binding protein (CD27BP), has been demonstrated to play opposite roles: (1) it is activated by the p53 and has pro-apoptotic activities in various cell lines [17,18], (2) it harbors ARF E3 ubiquitin protein ligase activity which leads to p53 degradation through the upregulation of Hdm2 protein [19], (3) SIVA ablation prevented the development of non-small cell lung cancer in a mouse model [20] revealing its oncogenic role in the respiratory epithelium, and (4) it can also inhibit STATHMIN, a microtubule destabilizer that when phosphorylated by CamKII may impede EMT and migration [21].The above are just a few examples that indicate the wide-ranging functions SIVA can play pending on cellular contexts [22].
The current study reports that the SIVA-D160N mutation serves as a dominant negative mutation and can promote migration and invasion in breast (and ovarian) cancer cell lines in vitro and promote breast tumor growth in vivo either as tumor xenografts in immunodeficient mice or an immuno-competent syngeneic mouse model.

Human tissue collection
Tumor specimens included in this study (16 breast cancer pairs, 13 synchronous and 3 metachronous) were derived from the Oregon Health & Science University (OHSU) Knight Cancer Institute Breast Cancer Repository that contained about 2000 samples [23].These tumors, deidentified and non-traceable, were originally submitted by community hospitals in Oregon, Washington, and Alaska to the College of American Pathologists-certified OHSU Hormone Receptor Laboratory between 1985-1998, in accordance with relevant guidelines and regulations.Breast tumors were snap-frozen within 30 min of biopsy or mastectomy, and continuously maintained frozen at -80˚C.All experimental protocols were carried out in accordance with relevant regulations: waiver of informed consent for the study and HIPAA authorization for research was approved by the by the Institutional Review Boards at OHSU and VA and community hospitals in accordance with federal and local privacy laws (OHSU IRB# 00000211, VA IRB# LUOH3850), all medical samples were de-identified and not traceable, last time data were accessed for research purposes was November 2023.Metachronous bilateral breast cancers were defined as bilateral breast cancers that are diagnosed at least 12 months apart.Systematic therapy was given to some patients with metachronous bilateral breast cancers after first cancer was diagnosed.The pathological diagnosis of specimens was confirmed by pathologists.

Genomic sequencing and analysis
Genomic DNA isolation from the tumors, library construction and sequencing were done by the OHSU Massively Parallel Sequencing Shared Resource on campus (Illumina sequencing) [24] per standard protocols in accordance with institutional regulations and IRB approved protocols.Because of the lack of germline controls, a comparative subtractive analysis was performed between the two tumors from the same patient (right compared with left, and left compared with right) and a subtraction of common variants from the single nucleotide polymorphisms database (dbSNP) and difficult to sequence regions.
In order to detect mutants and discover copy number variants, took HiSeq paired-end reads were aligned to the hg19 human reference genome using bwa mem [25], converting the sam format to bam (binary) format using samtools import (SAMTOOLS, RRID:SCR_002105).After sorting and indexing the reads in the bam formatted file, Picard Tools (MarkDuplicates, [26]) was used to remove duplicate reads generated during the PCR amplification stage.Duplicate removal was done by finding all reads that have identical 5' coordinates and keeping only the read pair with the highest map quality.After duplicate removal, reads around SNVs and indels were realigned using the GATK Software Library (GATK, RRID:SCR_001876) [27,28].Local positions to target for realignment were called using RealignerTargetCreator and the reads were realigned using IndelRealigner.Finally, quality scores were recalibrated.This was done using GATK BaseRecalibrator and PrintReads, [29], which binned reads based on the original quality score, the dinucleotide, and the position in the read.To call mutations we compared the tumor samples with the normal samples using muTect [30].Copy number analyses were done using CNVkit [31].Briefly, the average coverage per exon as well as off-target regions was found, normalized for the number of reads in the sample and for GC content, and then compared to the normal coverage.
A uniquely acquired mutation in one tumor was defined as having at least 30 independent reads with more than 20% of the reads carrying this mutation in comparison with having at least 10 independent reads over the same genomic segment with fewer than 2% of the reads carrying the same mutation in the contralateral tumor of the same patient.To assess clonal relationship, the copy number segments of different samples was compared using Clonality [32], an R-based package.Likelihood ratios (LR) were generated based on similar gains and losses on chromosome arms.A high LR corresponds to segmentation data from two synchronous tumors that shows greater similarity than those of unrelated tumors and would be evidence of clonality.

Cell proliferation, migration and invasion assays
Cancer cell proliferation in vitro was determined by the Trevigen TACS1XTT Proliferation Assay (R&D Systems, Cat# 4891-025-K) according to manufacturer's instructions.Four 96-well plates were prepared/experiment, with 1500 (231L) or 750 (4T1) cells seeded in each well (100 μL volume) in triplicates, and proliferation measured at day 0, 2, 3 and 4. Cell migration and invasion (each in triplicates) were examined using the Boyden Chamber system (8 μm pore size, Fisher Scientific, Cat# 353097) and the cell Matrigel invasion system (8 μm pore size, Corning, Cat #354480) respectively.Briefly, 300K cells/well (6-well plate) were grown overnight in media + 10% FBS in a 37˚C + 5% CO 2 incubator, then washed with PBS, trypsinized, resuspended in media + 0.1% FBS, filtered (40 μM), and counted.For the migration assay, 43500 cells in 300ul media + 0.1% FBS were carefully added to the migration inserts, placed in warmed 24-well plates containing 750 μl media + 10% FBS/well, and incubated for 6 hours at 37˚C + 5% CO 2 .For the invasion assay, 37500 cells in 300 μl media + 0.1% FBS were added to pre-warmed inserts and incubated in 750 μl media + 10% FBS for 24 hours at 37˚C + 5% CO 2 .Following incubations, migration and invasion inserts were transferred into Crystal violet solution for 20 minutes at RT to fix and stain cells, and then rinsed thoroughly in beakers with di-ionized water.Inserts were carefully cleaned on the inside (Q-tips) to remove excess of cells that did not migrate, without touching the outside of the mesh (where the cells migrated to).Inserts were let dry overnight, imaged (4 images/insert), and cells counted (for each experiment, cells for 4 images were added up).

Animals and housing
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health.The use and care of animals used in this study follows the guidelines of the VA Institutional Animal Care and Use Committee (Ethics approval code 3181-17, to SWL), and the study is in accordance with the ARRIVE guidelines (https://arriveguidelines.org).All efforts were made to minimize suffering: 1) procedures were performed under isoflurane anesthesia, 2) if a tumor measured larger than 1.5 cm 3 , or significant changes in body weight, body posture or reduced mobility were observed, this animal would be euthanized, 3) euthanasia was done by CO 2 exposure according to IACUC guidelines.

Tail vein injections (MB-MDA-231L), IVIS imaging and analysis
Empty vector (control), SIVA-WT and SIVA-D160N stably transfected MB-MDA-231L (luciferase, 231L) cell cultures were trypsinized, resuspended in ice-cold sterile PBS, filtered through a 40 μm cell strainer and quantified.7-week-old NOD-scid mice (19.12±0.34g/animal) were put under a red light for 10 minutes to dilate their tail veins, and then immediately injected into the lateral tail vein with 200 μL PBS containing 25K cells.Injections were performed by an experienced investigator, who randomly assigned the cells to each group.Luciferase-expressing cell spread was followed biweekly (Tuesdays and Thursdays) starting 5 days post-injection, and for a total of 3 weeks.For IVIS imaging, mice were injected with 100 μL of D-luciferin potassium salt (1.5 mg per 10 g animal in 100 μL sterile PBS; Goldbio, Cat# LUCK-1G) and 3 minutes after luciferin injection, the mice were anesthetized using inhaled isoflurane and positioned ventral side up on a heated platform.IVIS imaging was performed by an investigator blinded to the treatment.Bioluminescent images (exposure times were 3s and 60s) were obtained using an IVIS Spectrum CT and processed using Living Image software (RRID: SCR_014247; Perkin Elmer).All animals were euthanized by CO 2 inhalation after the last IVIS imaging.No animals were lost in the study nor excluded.

Fat-pad injections (4T1), tumor measurements and analysis
Empty vector (EV as control), SIVA-WT and SIVA-D160N stably transfected 4T1 cell cultures were trypsinized, resuspended in ice-cold sterile PBS, filtered through a 40 μm cell strainer and quantified.7-week-old Balb/c mice (17.14±0.29 g/animal) were anesthetized with isofluorane injected with 200 μL of PBS:matrigel (1:1; Matrigel) containing 25K cells into the fourth mammary gland fat pads.Injections were performed by an experienced investigator, who randomly assigned the cells to each group.Tumor formation was monitored thrice weekly (Monday, Wednesday, Friday) starting 5 days post-injection using a caliper (length and width), by two alternating investigators, for a total of 3 weeks.To minimize animal suffering, if a tumor measured larger than 1.5 cm 3 , or significant changes in body weight, body posture or reduced mobility were observed, this animal would be euthanized.At the end of the study, and the tumors were dissected out, measured, fixed in formalin for 24 hours and stored in 70% ethanol at 4˚C until paraffin embedding.5 μm thick sections from each representative specimen were obtained and processed for H&E and immunostaining.All animals were euthanized by CO 2 inhalation after the last tumor measurement (21 days post-injection).No animals were lost in the study nor excluded.

Immunocytochemistry (ICC) and Immunohistochemistry (IHC)
Antibodies: anti-SIVA (Atlas Antibodies Cat# HPA065398, RRID:AB_2685484, pRabbit), Ki67 (Ventana Medical Systems Cat# 790-4286, RRID:AB_2631262).ICC (SIVA) was done on 231L and 4T1 cell cultures grown on 8 mm coverslips in 24-well plated, fixed for 20 minutes with 4% paraformaldehyde/4% sucrose in PBS at RT and followed by washes in PBS.Cells were permeabilized with 0.3% Triton X-100 in PBS for 5 minutes at RT, followed by PBS wash.Slides were incubated in blocking buffer (0.5% BSA in 0.1 M Tris/0.15M NaCl) for 30 minutes at RT, followed by the incubation with anti-SIVA antibody (pRabbit, 1:1000) in 0.1% BSA/ 0.25% Triton X-100 blocking solution) for 24 hours at 4˚C in a humid chamber.Slides were then developed using the Vectastain Elite ABD HRP kit (Vector Labs, Cat# PK-6101) and the ImmPACT DAB chromogen (Vector labs, Cat# SK-4105) kit following manufacturer's instructions.Cells were counterstained with Hematoxylin according to standard protocols and mounted using Epredia™ Cytoseal™ Mountant XYL (Fisher Scientific, Cat# 22-050-262).IHC (Ki67) on tumor tissues was done as described by the manufacturer's instructions Briefly, deparaffinization was done in xylene followed by rehydration through a descending series of ethanol, antigen retrieval was done in citrate buffer pH 6 for 1 hour, blocking was done in 5% goat serum protein blocker for 4 minutes, Ki67 antibody incubation was done at @37˚C for 16 minutes, and DAB staining for 2 minutes.Finally, Ventana hematoxylin I counterstain was done for 4 minutes, and Ventana bluing reagent counter stain 4 minutes.Slides were mounted using Epredia™ Cytoseal™ Mountant XYL.Images were taken on an AXIO imager.A2 microscope (Zeiss, White Plains, NY, USA), attached to an Axiocam ERc 5s camera, using the ZEN2-blue software.Results (5 images per tumor, 10 tumors for each treatment) were expressed as % of positive Ki67 cells relative to total number of cells (total counts of hematoxylin-stained nuclei).

TUNEL assay
Apoptotic activity was analyzed TUNEL assay, using the ApopTag1 Plus peroxidase in situ apoptosis detection kit (EMD Millipore, Cat# S7101) according to the manufacturer's protocol.The positive TUNEL signals were counted under a AXIO imager.A2 microscopy (Zeiss, White Plains, NY, USA).Methyl green (Sigma, Cat# 67060) was used as counterstain.Apoptotic cells were calculated by averaging the 5 images per tumor (10 tumors for each group).

Statistical analysis
Results were expressed as mean ± standard error of the mean (SEM).All statistical analyses were performed with SAS software version 9.4 (SAS Institute, Cary, NC), and graphs were generated by R software [34] and GraphPad Prism 9 [35].Statistical differences between multiple groups were done using one-way ANOVA test followed by Tukey's or Dunnett's post-hoc tests (as indicated in figure legends).Statistical differences in tumor growth over time between multiple groups was done using two-way ANOVA (mixed effects) test followed by Tukey's posthoc test.Statistical differences in cell proliferation were assessed by simple linear regression test (proliferation independent variable is log scale).A p value of less than 0.05 was considered statistically significant.

Characterization of bilateral breast tumors and identification of the SIVA D160N mutation
Sixteen pairs of bilateral breast cancers were identified from a well-annotated breast cancer tissue repository (Knight Cancer Institute) of 2000 total samples (0.8%).Thirteen of them were synchronous and three metachronous.Thirteen pairs existed as frozen samples and three as pulverized.Demographics, histology, clinical staging, biomarker status, laterality, intervals between the detection of the two tumors and assessed clonal relationship are presented in Table 1.The depth of sequencing, i.e., the number of sequencing reads, is also presented in Table 1.Because no germ line controls were available, we performed a comparative subtractive analysis between the two tumors from the same patient (right compared with left and left compared with right) and a subtraction of common variants from the single nucleotide polymorphisms database (dbSNP) and difficult to sequence regions.A uniquely acquired mutation in one tumor was defined as having at least 30 independent reads with more than 20% of the reads carrying this mutation in comparison with having at least 10 independent reads over the same genomic segment with fewer than 2% of the reads carrying the same sequence change in the contralateral tumor of the same patient.The called variants were examined for overlap with known variants from publicly curated sets of breast cancer samples, and 1098 breast cancer samples from the TCGA-BRCA project located on the GDC Data Portal were used.For the samples in this study, we called variants without matched normal, filtering on dbSNP and requiring 0.20 VAF and 30x coverage, with an extensive exome sequencing coverage of at least 79x (Table 1; S1 Fig in S2 File).Furthermore, variants that were common between three or more samples were filtered out.A comparison of the fraction our samples with commonly mutated genes and the fraction of the TCGA set with those genes mutated is shown in Table A in S2 File.Many of the same genes were found to be mutated in our sample set were mutated in the TCGA-BRCA sample set.
Furthermore, when the PIK3CA mutations identified using the opposite tumor as a normal were examined, all mutations were found to be common breast cancer hotspots as identified by COSMIC.These included p.H1047R, p.E542K, and p.M1043I, listed in Table B in S2 File.Both above indicated common molecular profiles were shared between bilateral and unilateral breast cancers.
Clonal relationship was assessed by comparing the copy number segments of different samples in an all-against-all comparison for all tumors from all patients using the segmentation data (Fig 1A).Likelihood ratios (LR) were generated based on similar gains and losses on chromosome arms.A high LR corresponds to segmentation data from two synchronous tumors that show greater similarity than those of unrelated tumors and would be evidence of clonality, and the three tumor pairs (15L/15R, 8L/8R, 10L/10R) that show strong evidence for clonality are highlighted in Fig 1B .A heat map of copy number variation is shown in Fig 1C, where the 15L/15R, 8L/8R and 10L/10R tumor pairs show strong evidence of clonality based on comparison of their copy number segmentation ratio.
We then compared non-synonymous exonic mutations found in tumors from one side against their contralateral breast tumor from the same patient, identifying unique mutations present in one but not the contralateral tumor in these three patients: 0/0 (pair 10L/10R), 0/5 (pair 8L/8R), 5/8 (pair 15L/15R).In patient 8 the tumor on the right side was detected 32 months after the tumor on the left side, and the unique somatic mutations present on the right tumor were RYR3 (SNV, c.G7990A, p.E2664K), DDI1 (SNV, c.C107G, p.A36G), FCGRT (stop-gain, c.G155A, p.W52X), SIVA (SNV, c.G478A, p.D160N), SLC28A3 (SNV, c.G202A, p. E68K).The left and right breast tumors found in patient 8 showed strong evidence of clonality and the right sided tumor was found 32 months later than the left side, indicating that right sided tumor was a metastatic deposit from the left sided tumor.For the remainder of this study, we focused solely on the p.D160N mutation of the SIVA apoptosis inducing factor (SIVA-D160N), as deep deletion of SIVA was reported in 12% (36/301) of metastatic breast cancers [36], and SIVA downregulation promoted breast cancer cell aggressiveness both in vitro and in vivo [21].

Downregulation of SIVA in 231L cells significantly enhanced cell migration and invasion
SIVA protein has an amphipathic helical (SAH) region at the N-terminus, a death domain homology region (DDHR) in the middle, and the box-B-like ring finger and two zinc fingerlike cysteine rich domain at the C-terminus [37].Previous studies have identified the SAH and DDHR regions as essential for the pro-apoptotic function of SIVA [38].The mutation (c.In addition to generating the transient SIVA knockdowns, we used a lentivirus to express shRNA targeting the 3'-UTR of the SIVA to make a stable SIVA-knockdown (SIVA-KO) 231L cell line (Fig 2B).Migration and invasion of SIVA-KO cells showed a significant increase compared to 231L cells expressing the empty vector (264.8±36.1 and 549.4±54.6 vs 100.0±0.0,respectively; Fig 2C and 2D).Successful re-introduction of SIVA-WT protein was demonstrated by Western blot analysis (Fig 2B) which restored/abolished the migration and invasion phenotypes (95.5±19.2 and 237.4±23.7,respectively) displayed by the SIVA-KO cells (Fig 2C and 2D).Taken together, stable knockdown of SIVA in 231L cells significantly enhanced cell migration and invasion, effects that were reversed after re-introducing the expression of SIVA-WT.This highly suggests that SIVA is involved in the regulation of 231L cell mobility and invasiveness as previously reported in other cell lines such as breast MCF7 and colorectal HCT116 cells [21,42], and now validated in MB-MDA-231 cells.

Expression of SIVA-D160N mutant in 231L cells significantly enhanced cell migration and invasion, as well as tumor spread in vivo
We then set out to investigate the potential effect of the SIVA-D160N mutation in breast cancer cell proliferation, migration, and invasion, as well as tumor proliferation/spread in NSG-scid female mice.We stably expressed the empty vector (EV, control), SIVA-WT (WT) and SIVA-D160N (D160N) mutant constructs in 231L cells.The expression of SIVA protein in these cells was verified by Western blot analysis (Fig 2E).Migration analysis revealed a statistically significant increase in the SIVA-D160N expressing cells compared to the SIVA-WT expressing cells and the EV control (168.2±11.7 vs 67.4±5.6 and 100.0±0.0 respectively; Fig 2F).Invasion analysis revealed a statistically significant increase in the SIVA-D160N expressing cells compared to both, SIVA-WT and EV expressing cells (162.8±12.5 vs 73.7±5.0 and 100.0 ±0.0 respectively; Fig 2G).Interestingly, when we measured cell proliferation by XTT assays, simple linear regression analysis found that 231L cells expressing SIVA-WT and SIVA-D160N mutant displayed similar proliferation rates compared to EV control and SIVA-KO (simple linear regression analysis, p = 0.8788) (Fig 2H).Taken together, the expression of SIVA-D160N increased migration and invasion in 231L cells similarly to that of ablation of SIVA expression (KO), suggesting that SIVA-D160N serves as a dominant negative mutation that interferes with the wild type function of SIVA protein in 231L cells.
To investigate whether SIVA-D160N conferred increased metastatic potential, we used a xenograft model of metastasis.For this, we introduced 231L cells stably expressing EV (control), SIVA-WT and SIVA-D160N cells to immuno-deficient female NSG-scid mice via lateral tail vein injections (n = 5).The survival and expansion of these cells were then monitored twice weekly by serial IVIS imaging (Fig 2I).The luminescent intensity of photons emitted from each tumor was quantified, and tumors overexpressing SIVA-D160N mutation grew significantly faster than SIVA-WT or EV expressing control 231L cells (Fig 2J).Taken together, the above experiments showed that the SIVA-D160N mutation displayed metastasis promoting phenotype in breast cancer cell line 231L both in vitro and in vivo.

Expression of SIVA-D160N mutant in mouse 4T1 cells significantly increased metastasis in vivo
We then examined the impact of SIVA-D160N expression on mouse 4T1 mammary gland cancer cells, using a syngeneic mouse breast cancer model.We overexpressed empty vector (EV as control), SIVA-WT or SIVA-D160N mutation via plasmid mediated gene transfer in 4T1 cells and obtained polyclonal stable transfectants.The expression of SIVA protein in these 4T1 transfected cells was verified by Western blot analysis (Fig 3A).Migration analysis of 4T1 cells Interestingly, while culturing 4T1 cells for five days, we noticed that the cells expressing SIVA-D160N formed significantly more small and compacted 3D foci or aggregates (41.60 ±2.02 aggregates, vs. 5.90±0.70 and 4.20±0.51aggregates for SIVA-WT and EV, respectively; n = 10).This is an indication of anchorage-independent cell growth; this behavior was maintained even after filtering the 4T1 cells prior to seeding (Fig 3E and 3F We then introduced the 4T1 cell clones via orthotopic mammary fat pad injection into syngeneic female animals of Balb/c background and serially monitored the growth of the mammary gland tumors via a caliper.Mammary fat pad SIVA-D160N tumors grew significantly faster compared to EV control and SIVA-WT tumors, with the last two growing at identical rates (n = 10, Fig 4A).The size of the SIVA-D160N tumors after dissection was also significantly larger (0.724±0.057 g) than 4T1 cells expressing EV or SIVA-WT (0.436±0.045 and 0.470±0.049g, respectively; n = 10) (Fig 4B).There was no difference in the animal weights at the time of dissections (17.64±0.45(EV), 17.79±0.42(WT) and 17.58±0.44(D160N) g; n = 10, p = 0.9363).In addition, we determined apoptosis in these tumors by TUNEL assay to identify cells with nuclear DNA fragmentation.Cells were scored as apoptotic when they showed brown staining (TUNEL positive), compared to the methyl green counterstaining (TUNEL negative) (S5B Fig in S2 File).Quantification of the number of apoptotic cells showed a significant decrease in the TUNELpositive cells in the tumors expressing SIVA-WT (1.836±0.255%)compared with control (EV) and SIVA-D160N expressing cells (3.667±0.382%and 4.372±0.531%,respectively; n = 10; Fig 4D).
Mouse 4T1 cancer cells can form visible metastatic nodules in the lung and liver tissues.While we did not detect metastasis in the lungs, livers from control EV, SIVA-WT and SIVA-D160N expressing 4T1 cell tumor-bearing mice showed presence of metastatic deposits macroscopically (not shown).We examined the liver sections stained with H&E microscopically.We expressed the area occupied by the total metastatic lesions area relative to the liver area examined, with the livers from SIVA-D160N expressing tumors being significantly larger (0.211±0.068%) compared to EV and SIVA-WT expressing tumors (0.042±0.012% and 0.084 ±0.021%, respectively; p = 0.0352; n = 5;

SIVA-D160N mutation increases migration and invasion in additional breast (HCC1954) and ovarian (SKOV3, OVCAR8) cancer cells
Though the incidence of single nucleotide mutation in SIVA in breast cancer was low, a survey of The Cancer Genome Atlas (TCGA; [43]) via the Genomic Data Commons Data Portal found that 19% (204/1063) of primary breast cancers and 23% (129/560) of primary ovarian cancers had loss of copy numbers of SIVA.Other tumor types that had copy number loss of greater than 30% of the cases included cholangiocarcinoma (55.6%, 20/36), mesothelioma (40.7%, 35.86), renal clear cell carcinoma (37.3%, 193/517), and rectal adenocarcinoma (35.3%, 59/167).The above suggested a more global role of SIVA in cancer biology.
As SIVA is known to interact with multiple signaling molecules, its copy number reduction may have pleiotropic effects in cancer biology by affecting myriad interactions simultaneously.In this regard, SIVA-D160N mutation represents a rare opportunity when a circumscribed spectrum of pathways is expected to be affected by a single amino acid substitution, affording a unique opportunity to study the signaling pathway(s) governed by D160N in SIVA that mediated increased breast cancer aggressiveness in vivo and in vitro.
To broadly assess the functional outcome of over-expressing SIVA-WT and SIVA-D160N compared to control (EV) across multiple cell lines, additional stable polyclonal transfectants of these expression vectors were achieved in human breast cancer (HCC-1954) and ovarian cancer (SKOV3 and OVCAR8) cell lines.Western analysis confirmed the expression of the respective proteins in stable transfectants (S6A Fig in S2 File).Over-expression of SIVA-WT significantly decreased migration in all three cell lines when compared to control EV (S6B Fig in S2 File).SIVA-D160N expressing cells increased invasion (S6C Fig in S2 File) when compared when compared with EV expressing cells, respectively in all three cell lines as in 231L.In summary, a direct comparison between EV and SIVA-D160N overexpression consistently showed a significant increased invasion in the cell expressing the SIVA-D160N across four human cancer cell lines tested (and three for migration).These observations support a broader involvement of wild type SIVA and D160N mutation in the aggressiveness of cancer cells.We have performed RNAseq experiments to understand the signaling pathways downstream of SIVA-D160N mutation.Due to the exploratory nature of these experiments, the results are presented in the supplemental section (S3 File).

Discussion
Synchronous bilateral breast cancer cases (as defined by diagnoses less than two months apart) had worse breast cancer specific survival than the unilateral breast cancer cohort because of the higher-risk cancers of the bilateral breast cancer cases.In a matching analysis, breast cancer specific survival was equivalent for the synchronous bilateral breast cancer cases and their high-risk matches.Thus, for a patient with synchronous bilateral breast cancers, an appropriate systemic therapy selection can be made by considering the prognosis of their higher-risk cancer [44].Multiple somatic mutations that were commonly described in sporadic unilateral breast cancers were also observed in bilateral breast cancers in the present study (Table A in S2 File).The above clinical and genetic analyses indicate bilateral breast cancers share similar biology and clinical behaviors as unilateral breast cancers.
SIVA is a proapoptotic protein originally identified by virtue of its interaction with CD27 and other death receptors [16,45].The current literature suggests SIVA is pro-apoptotic and capable of inhibiting the growth of malignant tumors in breast [21], cervical [39,46], ovarian [40], colorectal [47] and acute leukemia [48] cancers, but anti-apoptotic and carcinogenic in non-small cell lung cancer [20], osteosarcoma [49] and gastric [38] cancers.SIVA therefore has a role as pro-or anti-malignant factor, depending on the cellular context.
In studies done using cell lines, SIVA was shown to be a direct p53 target gene that is specifically upregulated relative to G1 cell-cycle arrest to promote apoptosis [17,18], suggesting that SIVA may itself have a tumor-suppressor function.On the other hand, SIVA has been reported to suppress p53 activity by stabilizing the interaction between MDM2 and p53, leading to increased p53 ubiquitination and degradation, and increased bromodeoxyuridine (BrdUrd) incorporation [19,49], indicating that SIVA could also play a tumor-promoting role, further validating that the role of SIVA varies with cellular context.
Earlier studies using animal models showed that conditional inactivation of Siva in an autochthonous oncogenic KRASG12D-driven mouse model for non-small cell lung cancer (NSCLC) decreased tumor numbers and tumor burden relative to Siva-expressing controls.The SIVA knockdown also inhibited proliferation and transformation in both mouse and human NSCLC cells in vitro.The enhancement of tumorigenesis by SIVA relates to its ability to promote mTOR signaling, inhibit autophagy, and augment metabolic activity [20].On the contrary, nude mice injected with MCF7-SIVA shRNA cells exhibited markedly increased tumor metastasis compared to mice injected with MCF7-control shRNA cells.Analysis of tumors in lungs and livers further verified the highly enhanced metastatic potential of MCF7-SIVA shRNA cells [21].This study showed that SIVA counteracted STATHMIN, an important regulator for microtubule dynamics, and defined a role for SIVA in the suppression of EMT and tumor metastasis [21].A subsequent study showed that the overexpression of SIVA inhibited proliferation, promoted apoptosis and suppressed migration and invasion by facilitating phosphorylation of Stathmin and polymerization of α-tubulin in ovarian and cervical cancer cells [39,40].
Our current study suggested that SIVA-D160N functioned as a dominant negative mutation.This is based on the observation that over expression of wild type SIVA in human breast and ovarian cancer cell lines generally suppressed the migration and/or invasion; and overexpression of SIVA-D160N enhanced migration and/or invasion, in a manner like what we expect with SIVA knockdown with shRNA over expression.The signaling function(s) that are dependent on the aspartic acid at the position 160 of the wild type SIVA protein appeared to impart an anti-aggressive function, which was reversed by the D160N mutation, and appears to be different in different cell lines.In addition to increased invasion, there was also an increase in anchorage independent growth in mouse 4T1 cells.With no crystal structure currently available for SIVA, and based on a predictive model (http://www.sbg.bio.ic.ac.uk/), we can only hypothesize that the D160N mutation, located near/within the Zing-finger domain, may have disrupted a D160-K164 salt bridge, affecting the SIVA protein stability or specificity of the protein-protein interactions.However, exactly how the SIVA-D160N mutation affects the SIVA protein and its function, and how this perturbation by D160N mutation affects cancer metastasis is not yet known, and this is a limitation of the study.Protein molecules that can interact with this C-terminal segment of SIVA are worthy of further investigation with reduced complexity.
As SIVA is known to interact with multiple signaling molecules, its copy number reduction may have pleiotropic effects in cancer biology by affecting myriad interactions simultaneously.In this regard, SIVA-D160N mutation represented a rare opportunity when a circumscribed spectrum of pathways is expected to be affected by a single amino acid substitution, affording a unique opportunity to study the signaling pathway(s) governed by D160N in SIVA that mediated increased breast cancer aggressiveness in vivo and in vitro.Of note, over expression of wild type SIVA decreased rather than increased the apoptosis of 4T1 cells when introduced via orthotopic mammary fad pad injection in a syngeneic mouse model.This anti-apoptosis function was lost with the D160N mutation, suggesting an additional functional involvement of this segment in the suppression of apoptosis.This observation also suggested that the tumor aggressiveness promoting functions of SIVA-D160N in the 4T1 models was not associated with apoptosis.
Alteration in SIVA was rarely seen in primary breast cancer (less than 1% in TCGA).Deep deletion of SIVA was reported in 12% (36/301) of metastatic breast cancer, both receptor positive and receptor negative [50].AKT1 was also deleted as AKT1 and SIVA genes were in close proximity on the chromosome 14.The serine/threonine kinase AKT is frequently hyperactivated in breast cancer through multiple mechanisms, including PI3K activation, PTEN loss, and ErbB2/Her2/neu activation/amplification [51].Inducible ablation of Akt1 in mammary epithelium after mammary tumors were formed inhibited tumor growth but not metastasis [36].AKT1 therefore did not appear to be the target for deletion while SIVA was.Taken together, these results indicate that the loss of SIVA function, via either deletion or D160N mutation, may promote breast cancer metastasis.

Conclusions
Some of the bilateral breast cancers are clonally related, therefore representing breast-to-breast metastasis.Whole exome sequencing and comparative analysis of clonally related breast cancers from the same individual revealed that a very small number of somatic mutations was acquired in this breast-to-breast metastasis.One such mutation is D160N in SIVA.Our finding indicated that D160N functioned in a dominant negative function and promoted cancer spread in both in vitro and in vivo system.SIVA gene was deleted in 12% of metastatic breast cancer but SIVA aberration was rarely observed in primary breast cancer, suggesting a role of SIVA in cancer metastasis.Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.
G483A) in SIVA led to the substitution of Aspartic acid with the more polar amino acid Asparagine (p.D160N) in exon 4, near the C-terminal region of the protein (Fig 2A).Based on a predictive alphafold model (www.sbg.bio.ic.ac.uk/) due to the lack of a SIVA crystal structure, D160 is located in the Zing-finger domain, forming a D160-K164 salt bridge.The D160N mutation may disrupt this salt bridge, affecting the SIVA protein stability or specificity of protein-protein interactions (S2 Fig in S2 File).Since cell migration and invasion are hallmarks of cancer cell invasiveness, ([21,39-41], we first verified the role of SIVA in breast cancer MB-MDA-231 (expressing luciferase, 231L) cell migration and invasion.For this, we transiently downregulated the endogenous SIVA protein by siRNA transfection, leading to a significant enhancement in the migration and invasion capabilities of the 231L cells (S3 Fig in S2 File).

Fig 1 .
Fig 1. Clonality and copy number profiles.(A) Schematic description of the clonality tool.Top: Each red circle represents one breast cancer sample, and following segmentation, the log2 ratios for each sample are compared all against all to generate a set of correlations from known unrelated tumors, with N(N-1)/2 patient comparisons for reference.Bottom: For samples from the same patient, a higher correlation between the two tumors (red arrows) compared to the correlation for unrelated samples (black arrows) is taken as evidence of clonality.(B) Clonal relationship of bilateral breast cancers.The distribution of logLR (LR = likelihood ratio) among comparisons of unrelated samples (gray) or tumors from the same patients (red) is shown along the x-axis, while y-axis show the case counts.The positions of three tumor pairs (15L/15R, 8L/8R, 10L/10R) that show strong evidence for clonality are highlighted (*).(C) Copy number profiles showing gains (red) and losses (blue) for all the bilateral breast cancers.15L/15R, 8L/8R, and 10L/10R (arrows) show strong evidence of clonality based on comparison of their copy number segmentation ratio.https://doi.org/10.1371/journal.pone.0302856.g001

Fig 2 .
Fig 2. SIVA knockdown and SIVA-D160N mutation increased migration and invasion capabilities on 231L cells.(A) Schematic of SIVA protein showing the position (red line in exon 4) of point mutation identified in the "breast to breast" spread in patient 8. Domains: Amphipathic helix (SAH), death domain homology region (DDHR), cysteine rich domains (Cys-rich).(B) Stable knockdown of SIVA protein expression by shRNA (KO) and reintroduction of SIVA-WT protein (WT*), compared to endogenous (end) SIVA expression in empty vector control cells (EV) was demonstrated by Western blot analysis.(C) 231L cell migration (Boyden Chamber) and (D) 231L cell invasion (Matrigel matrix invasion) analyses were expressed as total cell counts in four fields of view (4 fov) normalized against EV control.Each bar represents the mean ± S.E.M (n = 3, total cells in 4 images/assay); One-way ANOVA (C: p = 0.0035 and D: p = 0.0.0002)followed by Tukey's post-hoc test.(E) Overexpression of SIVA-WT (WT) and mutated SIVA (D160N) protein, compared to endogenous SIVA levels in EV control 231L cells was demonstrated by Western blot analysis.(F) Cell migration and (G) cell invasion analyses of 231L cells overexpressing wild type SIVA (WT) and SIVA mutation (D160N) were expressed as in (C, D).One-way ANOVA (F: p = 0.0002, G: p = 0.0005).(H) Proliferation XTT assays, each point represents the mean ± S.E.M (n = 2, 6 replicates/assay); simple linear regression (p = 0.8788).(I) SIVA-D160N expressing 231L cells increased spread of breast cancer cells in immuno-deficient NSG mice.25K cells were injected into the lateral tail veins of female NSG mice (n = 5), and the proliferation and spread monitored by serial in vivo imaging (IVIS).Exposure times are 60s and 3s for 7 days and 21 days respectively.Luminescence counts is indicated in colored bar on the y-axis.(J) Absolute luminescent intensity of photons emitted from spreading tumor cells in each animal in the IVIS images (I) was quantified.Each line represents the mean ± SEM (n = 5).Mixed-effects analysis (p<0.0001) followed by Tukey's post-hoc test.Post Test p values: *p<0.05,**p<0.01,***p<0.001.https://doi.org/10.1371/journal.pone.0302856.g002

Table 1 . Bilateral breast cancers used in this study.
Breast cancer tumor pairs (L = left, R = Right) were obtained from sixteen patients, each patient pair is clustered in a row separated by lines from other patient tumor pairs.Three tumor pairs were not synchronous (sample ID 8, 10, 14), with the second contralateral tumor detected 32, 16 and 12 months after the first tumor.Rows with bold font indicate patients with tumors that showed strong evidence of clonality.NOS = invasive breast cancer not otherwise specified; IDC = invasive ductal carcinoma; DCIS = ductal carcinoma in situ; LOB = invasive lobular cancer; ND = not documented, ER = estrogen receptor; PR = progesterone receptor.https://doi.org/10.1371/journal.pone.0302856.t001